Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation | Paper Citation Record

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This paper cites Sim- to-real transfer for vision-and-language navigation.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Sim- to-real transfer for vision-and-language navigation

Reference 1

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This paper cites Blended latent diffusion.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Blended latent diffusion

Reference 2

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Unresolved cited work

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This paper cites Easily acces- sible text-to-image generation amplifies demographic stereo- types at large scale.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Easily acces- sible text-to-image generation amplifies demographic stereo- types at large scale

Reference 4

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This paper cites De- mystifying mmd gans.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation De- mystifying mmd gans

Reference 5

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Unresolved cited work

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This paper cites A multidimensional analysis of social biases in vision trans- formers.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation A multidimensional analysis of social biases in vision trans- formers

Reference 7

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This paper cites Would deep generative models amplify bias in future models? InProceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition, pages 10833–10843, 2024.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Would deep generative models amplify bias in future models? InProceedings of the IEEE/CVF Con- ference on Computer Vision and Pattern Recognition, pages 10833–10843, 2024

Reference 8

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This paper cites Reproducible scal- ing laws for contrastive language-image learning.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Reproducible scal- ing laws for contrastive language-image learning

Reference 9

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This paper cites A review of medical image data augmentation techniques for deep learning appli- cations.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation A review of medical image data augmentation techniques for deep learning appli- cations

Reference 10

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This paper cites Dall-eval: Probing the reasoning skills and social biases of text-to- image generation models.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Dall-eval: Probing the reasoning skills and social biases of text-to- image generation models

Reference 11

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This paper cites Large scale visual recognition challenge.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Large scale visual recognition challenge

Reference 12

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This paper cites Documenting large webtext corpora: A case study on the colossal clean crawled corpus.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Documenting large webtext corpora: A case study on the colossal clean crawled corpus

Reference 13

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This paper cites Image inpainting: A review.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Image inpainting: A review

Reference 14

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This paper cites Uncurated image-text datasets: Shedding light on demographic bias.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Uncurated image-text datasets: Shedding light on demographic bias

Reference 15

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This paper cites Facet: Fairness in computer vision evaluation benchmark.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Facet: Fairness in computer vision evaluation benchmark

Reference 16

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This paper cites Equality of op- portunity in supervised learning.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Equality of op- portunity in supervised learning

Reference 17

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This paper cites Prompt-to-prompt image editing with cross-attention control.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Prompt-to-prompt image editing with cross-attention control

Reference 18

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This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 19

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This paper cites Pas- cal voc 2008 challenge.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Pas- cal voc 2008 challenge

Reference 20

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This paper cites Social- counterfactuals: Probing and mitigating intersectional social biases in vision-language models with counterfactual exam- ples.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Social- counterfactuals: Probing and mitigating intersectional social biases in vision-language models with counterfactual exam- ples

Reference 21

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This paper cites Re- thinking fid: Towards a better evaluation metric for image generation.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Re- thinking fid: Towards a better evaluation metric for image generation

Reference 22

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This paper cites Segment any- thing.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Segment any- thing

Reference 23

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This paper cites Coco- counterfactuals: Automatically constructed counterfactual examples for image-text pairs.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Coco- counterfactuals: Automatically constructed counterfactual examples for image-text pairs

Reference 24

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This paper cites Microsoft coco: Common objects in context.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Microsoft coco: Common objects in context

Reference 25

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This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 26

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This paper cites Stable bias: Evaluating societal representa- tions in diffusion models.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Stable bias: Evaluating societal representa- tions in diffusion models

Reference 27

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This paper cites Mea- suring bias in multimodal models: Multimodal composite association score.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Mea- suring bias in multimodal models: Multimodal composite association score

Reference 28

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This paper cites HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models

Reference 29

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This paper cites Task2sim: To- wards effective pre-training and transfer from synthetic data.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Task2sim: To- wards effective pre-training and transfer from synthetic data

Reference 30

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This paper cites Synthmanticlidar: A synthetic dataset for seman- tic segmentation on lidar imaging.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Synthmanticlidar: A synthetic dataset for seman- tic segmentation on lidar imaging

Reference 31

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This paper cites Joint one-sided synthetic unpaired image transla- tion and segmentation for colorectal cancer prevention.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Joint one-sided synthetic unpaired image transla- tion and segmentation for colorectal cancer prevention

Reference 32

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This paper cites Self-supervised and semi-supervised polyp seg- mentation using synthetic data.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Self-supervised and semi-supervised polyp seg- mentation using synthetic data

Reference 33

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This paper cites Fair attribute classification through latent space de-biasing.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Fair attribute classification through latent space de-biasing

Reference 34

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Zero-shot text-to-image generation

Reference 35

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation SAM 2: Segment Anything in Images and Videos

Reference 36

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Morph: A longitudinal image database of normal adult age-progression

Reference 37

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This paper cites Playing for data: Ground truth from computer games.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Playing for data: Ground truth from computer games

Reference 38

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation High-resolution image synthesis with latent diffusion models

Reference 39

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Photorealistic text-to-image diffusion models with deep language understanding

Reference 40

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 41

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 42

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This paper cites Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Conceptual captions: A cleaned, hypernymed, im- age alt-text dataset for automatic image captioning

Reference 43

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This paper cites Ai models collapse when trained on recursively generated data.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Ai models collapse when trained on recursively generated data

Reference 44

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This paper cites A study on the distribution of social biases in self-supervised learning visual models.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation A study on the distribution of social biases in self-supervised learning visual models

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This paper cites A frame- work for synthetic image generation and augmentation for improving automatic sewer pipe defect detection.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation A frame- work for synthetic image generation and augmentation for improving automatic sewer pipe defect detection

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This paper cites Image representations learned with unsupervised pre-training contain human-like biases.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Image representations learned with unsupervised pre-training contain human-like biases

Reference 47

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This paper cites Exploiting cultural biases via homoglyphs in text-to-image synthesis.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Exploiting cultural biases via homoglyphs in text-to-image synthesis

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This paper cites Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views

Reference 49

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This paper cites Be- yond skin tone: A multidimensional measure of apparent skin color.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Be- yond skin tone: A multidimensional measure of apparent skin color

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This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Domain randomization for transferring deep neural networks from simulation to the real world

Reference 51

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Observation 47ccd5a2-238c-453d-9f9a-e89d21e193f2 · outbound

This paper cites Overwriting pre- trained bias with finetuning data.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Overwriting pre- trained bias with finetuning data

Reference 52

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This paper cites Measuring representational harms in image cap- tioning.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Measuring representational harms in image cap- tioning

Reference 53

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This paper cites Balanced datasets are not enough: Estimating and mitigating gender bias in deep image rep- resentations.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Balanced datasets are not enough: Estimating and mitigating gender bias in deep image rep- resentations

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.637842Z

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Observation 9a071c2f-e712-4fdd-89dd-4558fc51fbd7 · outbound

This paper cites Unsupervised Model Diagnosis.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Unsupervised Model Diagnosis

Reference 55

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This paper cites Im- proving clip fine-tuning performance.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Im- proving clip fine-tuning performance

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.618134Z

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Observation 7275d29b-1a22-4e42-ac68-5127d7014ebf · outbound

This paper cites Markedness in visual semantic ai.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Markedness in visual semantic ai

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.597807Z

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Observation 3dcbd0b2-911f-47bd-9090-c5efd90d23b7 · outbound

This paper cites Contrastive language-vision ai models pretrained on web- scraped multimodal data exhibit sexual objectification bias.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Contrastive language-vision ai models pretrained on web- scraped multimodal data exhibit sexual objectification bias

Reference 58

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Observation fd6b50a2-a4c6-4f0e-9194-3f2b26932caa · outbound

This paper cites Human preference score: Better aligning text- to-image models with human preference.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Human preference score: Better aligning text- to-image models with human preference

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.557658Z

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Observation ce2464a5-2b5f-454b-b566-dc0d99673063 · outbound

This paper cites Stable dif- fusion exposed: Gender bias from prompt to image.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Stable dif- fusion exposed: Gender bias from prompt to image

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.538999Z

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Observation f69d3b83-3576-443c-84a5-deb8a0adb618 · outbound

This paper cites Imagere- ward: Learning and evaluating human preferences for text- to-image generation.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Imagere- ward: Learning and evaluating human preferences for text- to-image generation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.520854Z

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Observation f8c3c5a0-2b85-453f-8dbb-946c3d23b592 · outbound

This paper cites Brushnet: A plug-and-play image inpainting model with decomposed dual-branch diffusion.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Brushnet: A plug-and-play image inpainting model with decomposed dual-branch diffusion

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.495325Z

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Observation e3f15598-af81-42f4-9884-4ad9a669e690 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Adding conditional control to text-to-image diffusion models

Reference 63

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Observation f6e42d7f-11cf-4a6d-8993-944d3ae0a525 · outbound

This paper cites Auditing Gender Presentation Differences in Text-to-Image Models.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Auditing Gender Presentation Differences in Text-to-Image Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-11T17:19:10.092097Z

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Observation 8da99029-0bb4-4345-8f9d-2c4321d76db7 · outbound

This paper cites Men also like shopping: Reducing gender bias amplification using corpus-level constraints.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Men also like shopping: Reducing gender bias amplification using corpus-level constraints

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.458641Z

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Observation 1a9f0f27-a8cd-4400-ba94-74b37c96a117 · outbound

This paper cites A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation A Task is Worth One Word: Learning with Task Prompts for High-Quality Versatile Image Inpainting

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T17:19:10.110270Z

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Observation 7b5761a9-e041-4cec-93f7-cd419b24cdab · outbound

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:19:10.439501Z

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Observation 41f1ec31-1082-4a15-8205-bb8a05d74e25 · outbound

This paper cites The original dataset contains annotations for 52 different occu- pations.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation The original dataset contains annotations for 52 different occu- pations

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.419122Z

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Observation 645c0d93-5bc5-4e45-aeac-a21dad889bb4 · outbound

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Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation Unresolved cited work

Reference 69

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:19:10.400149Z

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Observation d8380b9a-65b7-4c00-b600-e99a6e86a82a · outbound

This paper cites In this work, we focus on the gender counterfactuals, therefore, for each original cap- tion CO we produce a pair of captions CM and CW that correspond to the two genders.

Pinpoint Counterfactuals: Reducing social bias in foundation models via localized counterfactual generation In this work, we focus on the gender counterfactuals, therefore, for each original cap- tion CO we produce a pair of captions CM and CW that correspond to the two genders

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:19:10.375216Z

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